Construction of health forecast system using an aerosol forecast model.

2021 Fiscal Year Final Research Report

• Project/Area Number: 19K19468
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 58030:Hygiene and public health-related: excluding laboratory approach
• Research Institution: St. Luke's International University
• Principal Investigator: ONISHI Kazunari 聖路加国際大学, 専門職大学院公衆衛生学研究科(公衆衛生大学院), 准教授 (50596278)
• Project Period (FY): 2019-04-01 – 2022-03-31
• Keywords: 大気汚染 / 黄砂 / 健康予報 / 越境大気汚染 / アレルギー症状

Outline of Final Research Achievements

This study assessed the relationship between aerosol prediction model data in the global atmosphere acquired from the Japan Meteorological Agency and scores of subjective symptom investigation of inhabitants and evaluated its usefulness as an index for predicting short-term effects of Asan dust on health. In this study, firstly, it was shown from observation data that Asan dust, sulfuric acid, and nitric acid components were affected by cross-border air pollution. Next, it was suggested from the prediction data that the day of respiratory symptoms, throat symptoms, and nose symptoms caused by short-term exposure to Asian dust and other cross-border air pollution could be predicted 48 hours in advance. It was suggested that the modeled numerical data helped predict the health risk of cross-border air pollutants such as Asian dust and that MASINGAR could be applied and contribute to health prediction not only in Japan but also in the world because of the global model.

Free Research Field

環境疫学

Academic Significance and Societal Importance of the Research Achievements

これまで、環境研究として飛来予測がされていたが、そのデータと健康豚関係が本研究で明らかになった。大気汚染がひどい時に、体調の不具合や重篤なアレルギー症状を訴えることがあったが、48時間前の予測データを活用することで、前もって予防行動をとることができ、健康の悪化を防ぐことができる可能性が示唆された。
さらに、飛来した成分を調べることで、地元由来の汚染化越境由来の汚染かの区別ができ、自身の健康を左右する原因を特定し、大陸のイベントを鑑みながら効率よく対策と症状の評価が可能になった。また、マスクは、着用者次第で防御効果が左右されており、マスクの適切な選び方と使用方法に関する啓発の重要性が示された。